DDT exposure of frogs : a case study from Limpopo Province, South Africa

Amphibians are globally under pressure with environmental contaminants contributing to this. Despite caution aired more than 80 years ago of threats posed to amphibians by DDT spraying for disease vector control, no data have been published on concentrations or effects of DDT contamination in frogs from areas where DDT is actively sprayed to control the insect vectors of malaria. In this study, we sampled fat bodies of Xenopus laevis and Xenopus muelleri naturally occurring in an area where indoor residual spraying of DDT is employed and from adjacent, non-sprayed, areas. ΣDDT concentrations ranged between <LOQ and 280 ng/g ww (wet weight) from the non-sprayed area, and 5.5-910 ng/g ww from the sprayed area, but statistical significance could not be shown. We observed significant asymmetric testicular morphology in frogs from the sprayed area, possibly due to endocrine disruption by compounds such as the DDTs. A previous study from the same area found very high concentrations of DDT in the eggs of the Grey Heron Ardea cinerea. This suggests that the DDT we found in frogs may have contributed to DDT loadings higher in the food web. These findings, combined with other studies from this area, support the need to reduce and eventually move away from DDT in malaria control safely and sustainably.South African Water Research Commission (WRC) and the National Research Foundation (NRF).http://www.elsevier.com/locate/chemosphere2017-09-30hb2016School of Health Systems and Public Health (SHSPH

Increased caspase-3-dependent spermatogenic cell death and dysregulated adult spermatogenesis following in utero, lactational and direct exposure to para-nonylphenol

Abstract of the EUROTOX 2006/6 CTDC Congress - 43rd Congress of the European Societies of Toxicology & 6th Congress of Toxicology in Developing Countrie

A review and comparative study of cancer detection using machine learning : SBERT and SimCSE application

AVAILABILITY OF DATA AND MATERIALS : The data can be accessed at the host database (The European Genome-phenome Archive at the European Bioinformatics Institute, accession number: EGAD00001004582 Data access).BACKGROUND : Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various malignancies. Initially, a series of preprocessing steps and image segmentation steps are performed to extract region of interest features from noisy features. Then, the extracted features are applied to several machine learning and deep learning methods for the detection of cancer. METHODS : In this work, a review of all the methods that have been applied to develop machine learning algorithms that detect cancer is provided. With more than 100 types of cancer, this study only examines research on the four most common and prevalent cancers worldwide: lung, breast, prostate, and colorectal cancer. Next, by using state-of-the-art sentence transformers namely: SBERT (2019) and the unsupervised SimCSE (2021), this study proposes a new methodology for detecting cancer. This method requires raw DNA sequences of matched tumor/normal pair as the only input. The learnt DNA representations retrieved from SBERT and SimCSE will then be sent to machine learning algorithms (XGBoost, Random Forest, LightGBM, and CNNs) for classification. As far as we are aware, SBERT and SimCSE transformers have not been applied to represent DNA sequences in cancer detection settings. RESULTS : The XGBoost model, which had the highest overall accuracy of 73 ± 0.13 % using SBERT embeddings and 75 ± 0.12 % using SimCSE embeddings, was the best performing classifier. In light of these findings, it can be concluded that incorporating sentence representations from SimCSE’s sentence transformer only marginally improved the performance of machine learning models.The South African Medical Research Council (SAMRC) through its Division of Research Capacity Development under the Internship Scholarship Program from funding received from the South African National Treasury.https://bmcbioinformatics.biomedcentral.comam2024Computer ScienceSchool of Health Systems and Public Health (SHSPH)Non

Discriminatory Gleason grade group signatures of prostate cancer : an application of machine learning methods

One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1.The South African Medical Research Council (SAMRC) through its Division of Research Capacity Development under the Internship Scholarship Program from funding received from the South African National Treasury.http://www.plosone.orgdm2022Computer ScienceSchool of Health Systems and Public Health (SHSPH

African inclusion in prostate cancer genomic studies provides the first glimpses into addressing health disparities through tailored clinical care

No abstract available.Funding for genomic support provided by the National Health and Medical Research Council (NHMRC) of Australia.http://wileyonlinelibrary.com/journal/ctm2am2024School of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein

Effects of environmental endocrine disruptors, including insecticides used for malaria vector control on reproductive parameters of male rats

The male reproductive system is sensitive to endocrine disrupting chemicals (EDCs) during critical developmental windows. Male Sprague-Dawley rats were exposed in utero-, during lactation- and directly to 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT), 1,1,-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) and a mixture of DDT, deltamethrin (DM), p-nonylphenol (p-NP) and phytoestrogens, at concentrations found in a malaria-area. After dosing for 104 days, histological assessments and reproductive-endpoints were assessed. The anogenital distance (AGD) (P = 0.005) was shorter in the mixture-exposed group, while the prostate mass (P = 0.018) was higher in the DDT-exposed group. A higher testicular mass and abnormal histology was observed in the DDT-(P = 0.019), DDE-(P = 0.047) and mixture-exposed (P < 0.005) groups. This study shows that in utero-, lactational- and direct exposure to EDCs present in a malaria-area negatively affects male reproductive parameters in rats. These findings raise concerns to EDC-exposures to mothers living in malaria-areas and the reproductive health of their male offspring.Medical Research Council of South Africa2017-06-30hb2016PhysiologySchool of Health Systems and Public Health (SHSPH

The role of the PCA3 assay in predicting prostate biopsy outcome in a South African setting

OBJECTIVES • To evaluate the investigational role, ideal threshold and indications of the Prostate CAncer gene 3 (PCA3) assay in a South African context. • To better define the universality of the above marker since this is the pioneer study on the continent of Africa. PATIENTS AND METHODS • We prospectively evaluated 105 consecutive South African men referred for a prostate biopsy at two tertiary centres in the capital city, Pretoria. • Sequentially, PSA levels and post DRE urine samples were taken within 24 h before prostate biopsy. • The urine specimen was tested using the PROGENSA TM PCA3 assay and a score was generated as (PCA3 mRNA/PSA mRNA)× 1000. • The performance of this assay in predicting biopsy outcome was assessed, and compared with that of serum PSA. RESULTS • Median patient age was 67 years with a positive biopsy incidence of 42.9%. • The higher the PCA3 score the greater the probability of a positive biopsy ( P = 0.003). • This score performed independently of prostatic volume ( P = 0.3889) or the presence of a concurrent primary malignancy ( P = 0.804). • A threshold of 60 revealed a positive predictive value of 60% with an odds ratio of 4, whereas setting a limit of 35 revealed a positive predictive value of 54% and odds ratio of 3.5. • Using receiver operating characteristics for overall performance comparison, the PSA level (area under the curve 0.844) performed better than the PCA3 score (area under the curve 0.705). CONCLUSION • PCA3 assay has shown consistency and performed in line with previous studies but it did not surpass serum PSA in this population. • A PCA3 assay threshold of 60 performed better than the conventional limit of 35. • This assay may have a potential niche in a certain subset of South African men that includes patients with larger glands, previous negative biopsies and altered baseline PSA levels.IlexSA Medical and Lancet Laboratories (South Africa)

Anti-Müllerian Hormone and Lifestyle, Reproductive, and Environmental Factors Among Women in Rural South Africa

Few data exist regarding antiMüllerian hormone, a marker of ovarian reserve, in relation to environmental factors with potential ovarian toxicity

Revised timeline and distribution of the earliest diverged human maternal lineages in southern Africa

The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory. Our results confirm L0d as the earliest diverged lineage (∼172 kya, 95%CI: 149-199 kya), followed by L0k (∼159 kya, 95%CI: 136-183 kya) and a new lineage we name L0g (∼94 kya, 95%CI: 72-116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ∼93 kya (95%CI:76-112 kya). We concur the earliest emerging L0d1’2 sublineage L0d1b (∼49 kya, 95%CI:37-58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (∼17 kya, 95%CI:10-27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ∼21-17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a

Next generation mapping reveals novel large genomic rearrangements in prostate cancer

Complex genomic rearrangements are common molecular events driving prostate carcinogenesis. Clinical significance, however, has yet to be fully elucidated. Detecting the full range and subtypes of large structural variants (SVs), greater than one kilobase in length, is challenging using clinically feasible next generation sequencing (NGS) technologies. Next generation mapping (NGM) is a new technology that allows for the interrogation of megabase length DNA molecules outside the detection range of single-base resolution NGS. In this study, we sought to determine the feasibility of using the Irys (Bionano Genomics Inc.) nanochannel NGM technology to generate whole genome maps of a primary prostate tumor and matched blood from a Gleason score 7 (4 + 3), ETS-fusion negative prostate cancer patient. With an effective mapped coverage of 35X and sequence coverage of 60X, and an estimated 43% tumor purity, we identified 85 large somatic structural rearrangements and 6,172 smaller somatic variants, respectively. The vast majority of the large SVs (89%), of which 73% are insertions, were not detectable ab initio using high-coverage short-read NGS. However, guided manual inspection of single NGS reads and de novo assembled scaffolds of NGM-derived candidate regions allowed for confirmation of 94% of these large SVs, with over a third impacting genes with oncogenic potential. From this single-patient study, the first cancer study to integrate NGS and NGM data, we hypothesise that there exists a novel spectrum of large genomic rearrangements in prostate cancer, that these large genomic rearrangements are likely early events in tumorigenesis, and they have potential to enhance taxonomy.This work was supported by Movember Australia and the Prostate Cancer Foundation Australia (PCFA) as part of the Movember Revolutionary Team Award (MRTA) to the Garvan Institute of Medical Research program on prostate cancer bone metastasis (ProMis to P.I.C. and V.M.H.) dedicated to establishing NGM for clinically relevant prostate cancer, and the Australian Prostate Cancer Research Centre NSW (APCRC-NSW). Participant recruitment and sampling was supported by the Cancer Association of South Africa (CANSA to M.S.R.B and V.M.H.). W.J. is supported by APCRC-NSW, E.K.F.C. and D.C.P. are partly supported by ProMis, P.I.C. is supported by Mrs Janice Gibson and the Ernest Heine Family Foundation, Australia, and V.M.H. is supported by the University of Sydney Foundation and Petre Foundation, Australia.www.impactjournals.com/oncotargetam2018School of Health Systems and Public Health (SHSPH